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一种使用局部空间统计量的高分辨率影像显著结构提取方法

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武汉大学学报（信息科学版） 2014年第5期39卷 531-535页

作者：陈一祥秦昆冯霞武汉大学遥感信息工程学院湖北武汉430079

使用三个局部空间统计量(局部Moran’s I、局部Geary’s C和Getis)来建模影像的空间依赖性,提出了一种简单有效的获取影像显著结构的方法。该方法通过对空间依赖强度特征图像进行3D阈值化来获取影像的同质区或边缘结构,实验结果表明了... 详细信息

使用三个局部空间统计量(局部Moran’s I、局部Geary’s C和Getis)来建模影像的空间依赖性,提出了一种简单有效的获取影像显著结构的方法。该方法通过对空间依赖强度特征图像进行3D阈值化来获取影像的同质区或边缘结构,实验结果表明了这三个局部空间统计量在建模影像空间依赖性和获取显著结构方面的性能差异。

关键词：空间依赖局部空间统计量 3D阈值化结构

On propagation characteristics of SH-type surface acoustic waves in periodic metal gratings by variational principle

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Chinese Journal of Acoustics 2009年第2期28卷 129-136页

作者： XU Fangqian HE Shitang LIU Jiansheng chen yixiang Zhejiang Institute of Communication Media Hangzhou 310018 Institute of Acoustics Chinese Academy of Sciences Beijing 100190

Based on D.P. chen and Haus＇ theory, a theoretical method was presented to analyze dispersion characteristics of SH-type surface acoustic waves （SAWs） propagating on periodic metallic grating structures with a variational principle and coupling-of-modes equation. Without using complicated Green＇s function, the calculating results of the method agree well with those of Hashimoto＇s theory. On the other hand, Hashimoto＇s method is helpless for calculating the dispersion relation of short-circuited gratings on ST-90°X quartz etc. However, the method developed in this paper can successfully calculate it.

关键词： On propagation characteristics of SH-type surface acoustic waves in periodic metal gratings by variational principle SH type

Deep Factorization for Speech Signal

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Deep Factorization for Speech Signal

Deep Speaker Feature Learning for Text-independent Speaker Verification

第十四届全国人机语音通讯学术会议

作者： Dong Wang Lantian Li Ying Shi yixiang chen Zhiyuan Tang Center for Speech and Language Technologies Tsinghua University

Speech signals are complex intermingling of various informative factors,and this information blending makes decoding any of the individual factors extremely difficult.A natural idea is to factorize each speech frame into independent factors,though it turns out to be even more difficult than decoding each individual factor.A major encumbrance is that the speaker trait,a major factor in speech signals,has been suspected to be a long-term distributional pattern and so not identifiable at the frame *** this paper,we demonstrated that the speaker factor is also a short-time spectral pattern and can be largely identified with just a few frames using a simple deep neural network（DNN）.This discovery motivated a cascade deep factorization（CDF） framework that infers speech factors in a sequential way,and factors previously inferred are used as conditional variables when inferring other *** experiment on an automatic emotion recognition（AER） task demonstrated that this approach can effectively factorize speech signals,and using these factors,the original speech spectrum can be recovered with high *** factorization and reconstruction approach provides a novel tool for many speech processing tasks.

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Deep Speaker Feature Learning for Text-independent Speaker V...

Phone-aware Neural Language Identification

第十四届全国人机语音通讯学术会议

作者： Lantian Li yixiang chen Ying Shi Zhiyuan Tang Dong Wang Center for Speech and Language Technologies Tsinghua University

Recently deep neural networks（DNNs） have been used to learn speaker ***,the quality of the learned features is not sufficiently good,so a complex back-end model,either neural or probabilistic,has to be used to address the residual uncertainty when applied to speaker verification,just as with raw *** paper presents a convolutional timedelay deep neural network structure（CT-DNN） for speaker feature *** experimental results on the Fisher database demonstrated that this CT-DNN can produce high-quality speaker features:even with a single feature（0.3 seconds including the context）,the EER can be as low as 7.68%.This effectively confirmed that the speaker trait is largely a deterministic short-time property rather than a long-time distributional pattern,and therefore can be extracted from just dozens of frames.

关键词： deep neural networks speaker verification speaker feature

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Phone-aware Neural Language Identification

第十四届全国人机语音通讯学术会议

作者： Zhiyuan Tang Dong Wang yixiang chen Ying Shi Lantian Li Center for Speech and Language Technologies（CSLT） Tsinghua University

Pure acoustic neural models,particularly the LSTM-RNN model,have shown great potential in language identification（LID）.However,the phonetic information has been largely overlooked by most of existing neural LID models,although this information has been used in the conventional phonetic LID systems with a great *** present a phone-aware neural LID architecture,which is a deep LSTM-RNN LID system but accepts output from an RNN-based ASR *** utilizing the phonetic knowledge,the LID performance can be significantly ***,even if the test language is not involved in the ASR training,the phonetic knowledge stil-1 presents a large *** experiments conducted on four languages within the Babel corpus demonstrated that the phone-aware approach is highly effective.

关键词： language identification long short-term memory

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软件动态正确性的形式化描述

计算机研究与发展 2013年第3期50卷 626-635页

作者：马艳芳张敏陈仪香淮北师范大学计算机科学与技术学院安徽淮北235000 上海市高可信计算重点实验室(华东师范大学软件学院) 上海200062

软件正确性是一个逐渐改进的过程.通过不断地修改,软件越来越接近于正确.同时软件的执行依赖于环境.为了刻画软件的动态正确性并考虑环境的因素,以参数化互模拟为基础,利用极限的观点,建立软件动态正确性的形式化描述.首先建立参数化互... 详细信息

软件正确性是一个逐渐改进的过程.通过不断地修改,软件越来越接近于正确.同时软件的执行依赖于环境.为了刻画软件的动态正确性并考虑环境的因素,以参数化互模拟为基础,利用极限的观点,建立软件动态正确性的形式化描述.首先建立参数化互模拟的无限演化理论,给出参数化极限互模拟的定义,并给出几个特殊的参数化极限互模拟实例.其次,建立参数化互模拟极限,给出参数化互模拟极限的规约刻画.最后,证明参数化互模拟极限的唯一性、与参数化互模拟的相容性等代数性质.

关键词：软件正确性参数化互模拟形式化极限拓扑

Formation and evolution of supercritical geofluid

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Science China Earth Sciences 2024年

作者： Huaiwei NI Yilin XIAO Xiaolin XIONG Xiandong LIU Chunxiao GAO yixiang chen Yunguo LI Wancai LI Xuan GUO Yangyang WANG Dongbo TAN Li ZHANG State Key Laboratory of Lithospheric and Environmental Coevolution University of Science and Technology of China Deep Space Exploration Laboratory/School of Earth and Space Sciences University of Science and Technology of China Guangzhou Institute of Geochemistry Chinese Academy of Sciences School of Earth Sciences and Engineering Nanjing University State Key Lab of Superhard Materials Jilin University

In this work, we provide a comprehensive review on the formation, evolution, properties, and effects of supercritical geofluid. In Earth's interior, enhanced miscibility between H2O and silicate by the addition of special components or by the increase of pressure and temperature gives rise to supercritical geofluid with a significant amount of both H2O and silicate *** formation of supercritical geofluid in magmatic-hydrothermal systems, typified by pegmatite system, is governed by meltfluid critical curve. The formation of supercritical geofluid in metamorphic systems, typified by subducted slab, is governed by the second critical end point. Experimental results suggest that the presence of boron and fluorine in pegmatite system makes it possible to form supercritical geofluid at crustal depths, but the release of supercritical geofluid from subducted slab is withheld until almost 100 km depth. A major presence of both H2O and depolymerized structural units（monomers, dimers, etc.） endows supercritical geofluid with unique physical properties including low density, low elastic moduli, low viscosity, high diffusivity,and high electrical conductivity. Supercritical geofluid can effectively mobilize a variety of elements even including high field strength elements and heavy rare earth elements. The chemical signatures of supercritical geofluid can be inherited by metasomatized mantle and mantle-derived melts, and this could give an explanation of the oxidation of arc magmas. Phase separation of supercritical geofluid through the mechanism of spinodal decomposition leads to formation of a melt network. Multiphase fluid inclusions recovered from subduction zone rocks and pegmatites are possible relics of supercritical geofluid. Supercritical geofluid can cause electrical anomaly and low seismic velocity near the top of subducted slab, and can be linked with intermediate-focus earthquakes. Supercritical geofluid may have played a crucial role in the formation of pe

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耦合薄膜微电感绕组损耗解析算法

中国电机工程学报 2017年第21期37卷 6437-6444页

作者：董纪清陈义祥汪晶慧福州大学电气工程与自动化学院福建省福州市350108

工作于电压调节模块中的耦合薄膜微电感,耦合绕组的电流之间存有相位差,电流相位差使电感内的磁场分布发生改变,引起绕组损耗的显著变化。准确预测不同相位差与频率下的绕组损耗对于耦合薄膜微电感的设计及优化至关重要。该文在此背景... 详细信息

工作于电压调节模块中的耦合薄膜微电感,耦合绕组的电流之间存有相位差,电流相位差使电感内的磁场分布发生改变,引起绕组损耗的显著变化。准确预测不同相位差与频率下的绕组损耗对于耦合薄膜微电感的设计及优化至关重要。该文在此背景下分析了跑道型耦合薄膜微电感在不同电流相位差下的磁场分布情况,通过准确提取相应频率下的电阻矩阵,建立不同电流相位差下的绕组损耗解析算法。最后运用有限元仿真软件验证文中耦合薄膜微电感绕组损耗解析算法的准确性和实用性。

关键词：薄膜微电感绕组损耗相位差磁场分布

视觉显著性与知觉组织相结合的高分影像居民地提取方法

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测绘学报 2017年第12期46卷 1959-1968页

作者：陈一祥秦昆张晔袁媛南京邮电大学地理与生物信息学院江苏南京210023 安徽省智慧城市与地理国情监测重点实验室安徽合肥230031 武汉大学遥感信息工程学院湖北武汉430079

受人类视觉认知机制的启发,提出了一种利用视觉显著性与知觉组织相结合的高分辨率遥感影像居民地提取方法。首先利用认知物理学中的数据场构建居民地的视觉显著性模型,并通过自适应阈值法实现候选居民地的自动提取,然后利用多尺度小波... 详细信息

受人类视觉认知机制的启发,提出了一种利用视觉显著性与知觉组织相结合的高分辨率遥感影像居民地提取方法。首先利用认知物理学中的数据场构建居民地的视觉显著性模型,并通过自适应阈值法实现候选居民地的自动提取,然后利用多尺度小波变换的高频特征实现居民地的知觉组织,最后通过集合交运算提取同时满足这两种视觉机制的居民地。通过ZY-3和Quickbird两种高分传感器的影像数据集进行居民地提取试验,验证了该方法的有效性。

关键词：高分辨率遥感影像视觉显著性数据场知觉组织小波变换居民地提取